The appropriate selection of individuals or candidates for employment, appointment to political positions, promotions, receiving awards or scholarships, and so on has traditionally been a difficult problem.
One trend facing competition systems is that of ever-increasing numbers of applications being received by competition systems. This results in problems of data handling of selecting the best candidates from an ever-increasing number of highly-qualified applicants, and also of eliminating an ever-increasing number of lower-quality, ineligible, or incompletely-responsive candidates.
The problem of candidate selection is compounded by candidate fraud which is becoming increasingly sophisticated. The forging of documents, the use of documents or credentials of others having similar names or demographic information, and so on complicates competition systems due to the detection and resolution requirements which must be imposed, as well as the resultant unfairness when such fraud goes undetected.
Another problem is the occurrence of duplicate forms. This often occurs as individuals apply multiple times in order to correct information or perhaps even in the belief that this can aid their chances of success.
The detection of both duplicates and fraud is further complicated, however, in that situations arise where two or more legitimate candidates sometimes appear identical from their submitted papers. Such situations often arise in connection with twins having similar or identical names, for example.
The selection of candidates for positions of future responsibility such as political appointees, military or civilian officers or leaders, corporate management, academic scholars, and so on has at its root the problem of selecting the best candidate based on predicted future performance. Studies have shown that non-traditional variables such as non-cognitive variables are sometimes a better predictor of future performance than traditionally-used variables.
The use of these variables, as well as the use of traditional but subjective variables, such as essay tests, has a problem because the nature of their evaluation is subjective aid thus difficult, even for a single evaluator, to do in a fair and consistent manner. This problem increases with the number of evaluators and encompasses the problems of evaluator selection, training, and monitoring. Studies have shown for example, that evaluators sometimes vary their decision methodologies in their evaluations, especially just before breaks or at the end of the day. Further more, studies have also shown that evaluators may evaluate non-cognitive variables more harshly for candidates of one ethnic or cultural background as compared with candidates of other ethnic or cultural backgrounds. The monitoring of evaluators is additionally complicated as system generally don't have the infrastructure necessary to allow real-time monitoring in a non-invasive way or the ability to implement corrective measures in real-time.
Additionally, traditional systems are lacking in methodologies to track both competition winners and competition losers for later use in producing statistical support for and improvement of system selection criteria.
From the above, it is evident that improvements are needed in the areas of data management (i.e. duplicate identification, false-duplicate identification, and fraud identification), candidate pool reduction, evaluator management, candidate selection, and winning-candidate progress tracking.